Large-scale Galaxy Surveys Research Articles

Apparent Parity Violation in the Observed Galaxy Trispectrum.

Recent measurements of the four-point correlation function in large-scale galaxy surveys have found apparent evidence of parity violation in the distribution of galaxies. This cannot happen via dynamical gravitational effects in general relativity. If such a violation arose from physics in the early Universe it could indicate important new physics beyond the standard model, and would be at odds with most models of inflation. It is therefore now timely to consider the galaxy trispectrum in more detail. While the intrinsic four-point correlation function, or equivalently the trispectrum, its Fourier counterpart, is parity invariant, the observed trispectrum must take redshift-space distortions into account. Although the standard Newtonian correction also respects parity invariance, we show that subleading relativistic corrections do not. We demonstrate that these can be significant at intermediate linear scales and are dominant over the Newtonian parity-invariant part around the equality scale and above. Therefore when observing the galaxy four-point correlation function, we should expect to detect parity violation on large scales.

Simulation-based inference of deep fields: galaxy population model and redshift distributions

Accurate redshift calibration is required to obtain unbiased cosmological information from large-scale galaxy surveys. In a forward modelling approach, the redshift distribution n(z) of a galaxy sample is measured using a parametric galaxy population model constrained by observations. We use a model that captures the redshift evolution of the galaxy luminosity functions, colours, and morphology, for red and blue samples. We constrain this model via simulation-based inference, using factorized Approximate Bayesian Computation (ABC) at the image level. We apply this framework to HSC deep field images, complemented with photometric redshifts from COSMOS2020. The simulated telescope images include realistic observational and instrumental effects. By applying the same processing and selection to real data and simulations, we obtain a sample of n(z) distributions from the ABC posterior. The photometric properties of the simulated galaxies are in good agreement with those from the real data, including magnitude, colour and redshift joint distributions. We compare the posterior n(z) from our simulations to the COSMOS2020 redshift distributions obtained via template fitting photometric data spanning the wavelength range from UV to IR. We mitigate sample variance in COSMOS by applying a reweighting technique. We thus obtain a good agreement between the simulated and observed redshift distributions, with a difference in the mean at the 1σ level up to a magnitude of 24 in the i band. We discuss how our forward model can be applied to current and future surveys and be further extended. The ABC posterior and further material will be made publicly available at https://cosmology.ethz.ch/research/software-lab/ufig.html.

Predicting the Spectroscopic Features of Galaxies by Applying Manifold Learning on Their Broadband Colors: Proof of Concept and Potential Applications for Euclid, Roman, and Rubin LSST

Entering the era of large-scale galaxy surveys, which will deliver unprecedented amounts of photometric and spectroscopic data, there is a growing need for more efficient, data-driven, and less model-dependent techniques to analyze the spectral energy distribution of galaxies. In this work, we demonstrate that by taking advantage of manifold learning approaches, we can estimate spectroscopic features of large samples of galaxies from their broadband photometry when spectroscopy is available only for a fraction of the sample. This will be done by applying the self-organizing map algorithm on broadband colors of galaxies and mapping partially available spectroscopic information into the trained maps. In this pilot study, we focus on estimating the 4000 Å break in a magnitude-limited sample of galaxies in the Cosmic Evolution Survey (COSMOS) field. We also examine this method to predict the Hδ A index given our available spectroscopic measurements. We use observed galaxy colors (u,g,r,i,z,Y,J,H), as well as spectroscopic measurements for a fraction of the sample from the LEGA-C and zCOSMOS spectroscopic surveys to estimate this feature for our parent photometric sample. We recover the D4000 feature for galaxies that only have broadband colors with uncertainties about twice the uncertainty of the employed spectroscopic surveys. Using these measurements, we observe a positive correlation between D4000 and the stellar mass of the galaxies in our sample with weaker D4000 features for higher-redshift galaxies at fixed stellar masses. These can be explained by the downsizing scenario for the formation of galaxies and the decrease in their specific star formation rate as well as the aging of their stellar populations over this time period.

Galmoss: A package for GPU-accelerated galaxy profile fitting

We introduce galmoss, a python-based, torch-powered tool for two-dimensional fitting of galaxy profiles. By seamlessly enabling GPU parallelization, galmoss meets the high computational demands of large-scale galaxy surveys, placing galaxy profile fitting in the CSST/LSST-era. It incorporates widely used profiles such as the Sérsic, Exponential disk, Ferrer, King, Gaussian, and Moffat profiles, and allows for the easy integration of more complex models. Tested on 8289 galaxies from the Sloan Digital Sky Survey (SDSS) g-band with a single NVIDIA A100 GPU, galmoss completed classical Sérsic profile fitting in about 10 min. Benchmark tests show that galmoss achieves computational speeds that are 6 × faster than those of default implementations.

Detecting Anomalous Images in Astronomical Datasets

Environmental and instrumental conditions can cause anomalies in astronomical images, which can potentially bias all kinds of measurements if not excluded. Detection of the anomalous images is usually done by human eyes, which is slow and sometimes not accurate. This is an important issue in weak lensing studies, particularly in the era of large-scale galaxy surveys, in which image qualities are crucial for the success of galaxy shape measurements. In this work we present two automatic methods for detecting anomalous images in astronomical data sets. The anomalous features can be divided into two types: one is associated with the source images, and the other appears on the background. Our first method, called the entropy method, utilizes the randomness of the orientation distribution of the source shapes and the background gradients to quantify the likelihood of an exposure being anomalous. Our second method involves training a neural network (autoencoder) to detect anomalies. We evaluate the effectiveness of the entropy method on the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) and Dark Energy Camera Legacy Survey (DECaLS DR3) data. In CFHTLenS, with 1171 exposures, the entropy method outperforms human inspection by detecting 12 of the 13 anomalous exposures found during human inspection and uncovering 10 new ones. In DECaLS DR3, with 17112 exposures, the entropy method detects a significant number of anomalous exposures while keeping a low false-positive rate. We find that although the neural network performs relatively well in detecting source anomalies, its current performance is not as good as the entropy method.

Deblending overlapping galaxies in DECaLS using transformer-based algorithm: A method combining multiple bands and data types

Abstract In large-scale galaxy surveys, particularly deep ground-based photometric studies, galaxy blending was inevitable. Such blending posed a potential primary systematic uncertainty for upcoming surveys. Current deblenders predominantly depended on analytical modelling of galaxy profiles, facing limitations due to inflexible and imprecise models. We presented a novel approach, using a U-net structured transformer-based network for deblending astronomical images, which we term the CAT-deblender. It was trained using both RGB and the grz-band images, spanning two distinct data formats present in the Dark Energy Camera Legacy Survey (DECaLS) database, including galaxies with diverse morphologies in the training dataset. Our method necessitated only the approximate central coordinates of each target galaxy, sourced from galaxy detection, bypassing assumptions on neighbouring source counts. Post-deblending, our RGB images retained a high signal-to-noise peak, consistently showing superior structural similarity against ground truth. For multi-band images, the ellipticity of central galaxies and median reconstruction error for r-band consistently lie within $\pm$ 0.025 to $\pm$ 0.25, revealing minimal pixel residuals. In our comparison of deblending capabilities focused on flux recovery, our model showed a mere 1% error in magnitude recovery for quadruply blended galaxies, significantly outperforming SExtractor’s higher error rate of 4.8%. Furthermore, by cross-matching with the publicly accessible overlapping galaxy catalogs from the DECaLS database, we successfully deblended 433 overlapping galaxies. Moreover, we have demonstrated effective deblending of 63 733 blended galaxy images, randomly chosen from the DECaLS database.

As Simple as Possible but No Simpler: Optimizing the Performance of Neural Net Emulators for Galaxy SED Fitting

Artificial neural network emulators have been demonstrated to be a very computationally efficient method to rapidly generate galaxy spectral energy distributions, for parameter inference or otherwise. Using a highly flexible and fast mathematical structure, they can learn the nontrivial relationship between input galaxy parameters and output observables. However, they do so imperfectly, and small errors in flux prediction can yield large differences in recovered parameters. In this work, we investigate the relationship between an emulator’s execution time, uncertainties, correlated errors, and ability to recover accurate posteriors. We show that emulators can recover consistent results to traditional fits, with a precision of 25%–40% in posterior medians for stellar mass, stellar metallicity, star formation rate, and stellar age. We find that emulation uncertainties scale with an emulator’s width N as ∝N −1, while execution time scales as ∝N 2, resulting in an inherent tradeoff between execution time and emulation uncertainties. We also find that emulators with uncertainties smaller than observational uncertainties are able to recover accurate posteriors for most parameters without a significant increase in catastrophic outliers. Furthermore, we demonstrate that small architectures can produce flux residuals that have significant correlations, which can create dangerous systematic errors in colors. Finally, we show that the distributions chosen for generating training sets can have a large effect on an emulator’s ability to accurately fit rare objects. Selecting the optimal architecture and training set for an emulator will minimize the computational requirements for fitting near-future large-scale galaxy surveys. We release our emulators on GitHub (http://github.com/elijahmathews/MathewsEtAl2023).

The MillenniumTNG Project: the hydrodynamical full physics simulation and a first look at its galaxy clusters

ABSTRACT Cosmological simulations are an important theoretical pillar for understanding non-linear structure formation in our Universe and for relating it to observations on large scales. In several papers, we introduce our MillenniumTNG (MTNG) project that provides a comprehensive set of high-resolution, large-volume simulations of cosmic structure formation aiming to better understand physical processes on large scales and to help interpret upcoming large-scale galaxy surveys. We here focus on the full physics box MTNG740 that computes a volume of $740\, \mathrm{Mpc}^3$ with a baryonic mass resolution of $3.1\times ~10^7\, \mathrm{M_\odot }$ using arepo with 80.6 billion cells and the IllustrisTNG galaxy formation model. We verify that the galaxy properties produced by MTNG740 are consistent with the TNG simulations, including more recent observations. We focus on galaxy clusters and analyse cluster scaling relations and radial profiles. We show that both are broadly consistent with various observational constraints. We demonstrate that the SZ-signal on a deep light-cone is consistent with Planck limits. Finally, we compare MTNG740 clusters with galaxy clusters found in Planck and the SDSS-8 RedMaPPer richness catalogue in observational space, finding very good agreement as well. However, simultaneously matching cluster masses, richness, and Compton-y requires us to assume that the SZ mass estimates for Planck clusters are underestimated by 0.2 dex on average. Due to its unprecedented volume for a high-resolution hydrodynamical calculation, the MTNG740 simulation offers rich possibilities to study baryons in galaxies, galaxy clusters, and in large-scale structure, and in particular their impact on upcoming large cosmological surveys.

Uncorrelated compensated isocurvature perturbations from kinetic Sunyaev-Zeldovich tomography

Compensated isocurvature perturbations (CIPs) are relative density perturbations in which a baryon-density fluctuation is accompanied by a dark matter density fluctuation such that the total-matter density is unperturbed. These fluctuations can be produced primordially if multiple fields are present during inflation, and therefore they can be used to differentiate between different models for the early Universe. Kinetic Sunyaev-Zeldovich (kSZ) tomography allows for the reconstruction of the radial-velocity field of matter as a function of redshift. This technique can be used to reconstruct the total-matter-overdensity field, independent of the galaxy-density field obtained from large-scale galaxy surveys. We leverage the ability to measure the galaxy- and matter-overdensity fields independently to construct a minimum-variance estimator for the primordial CIP amplitude, based on a mode-by-mode comparison of the two measurements. We forecast that a configuration corresponding to CMB-S4 and VRO will be able to detect (at $2\sigma$) a CIP amplitude $A$ (for a scale-invariant power spectrum) as small as $A\simeq 5\times 10^{-9}$. Similarly, a configuration corresponding to SO and DESI will be sensitive to a CIP amplitude $A\simeq 1\times 10^{-7}$. These values are to be compared to current constraints $A \leq {\cal O}(0.01)$.

Constraining the Origin of Stellar Binary Black Hole Mergers by Detections of Their Lensed Host Galaxies and Gravitational Wave Signals

A significant number of stellar binary black hole (sBBH) mergers may be lensed and detected by the third generation of gravitational wave (GW) detectors. Their lensed host galaxies may be detectable, which would thus help to accurately localize these sources and provide a new approach to study the origin of sBBHs. In this paper, we investigate the detectability of lensed host galaxies for lensed sBBH mergers. We find that the detection fraction of galaxies hosting lensed GW events can be significantly different for a survey with a given limiting magnitude if sBBHs are produced by different mechanisms, such as the evolution of massive binary stars, dynamical interactions in dense star clusters, and production assisted by active galactic nuclei or massive black holes. Furthermore, we illustrate that the statistical spatial distributions of those lensed sBBHs in their hosts resulting from different sBBH formation channels can differ. Therefore, with the third generation of GW detectors and future large-scale galaxy surveys, it is possible to independently constrain the origin of sBBHs via the detection fraction of those lensed events with identifiable lensing host signatures and/or even to constrain the fractional contributions from different sBBH formation mechanisms.

Far-infrared imager and polarimeter for the Origins Space Telescope

The far-infrared imager and polarimeter (FIP) for the Origins Space Telescope (Origins) is a basic far-infrared imager and polarimeter. The camera will deliver continuum images and polarization measurements at 50 and 250 μm. Currently available detector technologies provide sufficient sensitivity for background limited observations from space, at least on a single pixel basis. FIP incorporates large next-generation superconducting detector arrays and our technology development plan will push the pixel numbers for the arrays to the required size of 8000. Two superconducting detector technologies are currently candidates for the instrument: transition edge sensors or microwave kinetic inductance devices. Using these detectors and taking advantage of the cryogenic telescope that is provided by Origins, FIP will achieve mapping speeds of up to eight orders of magnitude faster than what has been achieved by existing observatories. The science drivers for FIP include observations of solar system objects, dust properties, and magnetic field studies of the nearby interstellar medium, and large scale galaxy surveys to better constrain the star formation history of the universe to address one of the main themes of Origins: “How does the Universe work?” In addition to the science, the FIP instrument plays a critical functional role in aligning the mirrors during on orbit observatory commissioning.

Dynamic zoom simulations: A fast, adaptive algorithm for simulating light-cones

ABSTRACT The advent of a new generation of large-scale galaxy surveys is pushing cosmological numerical simulations in an uncharted territory. The simultaneous requirements of high resolution and very large volume pose serious technical challenges, due to their computational and data storage demand. In this paper, we present a novel approach dubbed dynamic zoom simulations – or dzs – developed to tackle these issues. Our method is tailored to the production of light-cone outputs from N-body numerical simulations, which allow for a more efficient storage and post-processing compared to standard comoving snapshots, and more directly mimic the format of survey data. In dzs, the resolution of the simulation is dynamically decreased outside the light-cone surface, reducing the computational work load, while simultaneously preserving the accuracy inside the light-cone and the large-scale gravitational field. We show that our approach can achieve virtually identical results to traditional simulations at half of the computational cost for our largest box. We also forecast this speedup to increase up to a factor of 5 for larger and/or higher resolution simulations. We assess the accuracy of the numerical integration by comparing pairs of identical simulations run with and without dzs. Deviations in the light-cone halo mass function, in the sky-projected light-cone, and in the 3D matter light-cone always remain below 0.1 per cent. In summary, our results indicate that the dzs technique may provide a highly valuable tool to address the technical challenges that will characterize the next generation of large-scale cosmological simulations.

Nonlocal entanglement and directional correlations of primordial perturbations on the inflationary horizon

Models are developed to estimate properties of relic cosmic perturbations with "spooky" nonlocal correlations on the inflationary horizon, analogous to those previously posited for information on black hole event horizons. Scalar curvature perturbations are estimated to emerge with a dimensionless power spectral density $\Delta_S^2\approx H t_P$, the product of inflationary expansion rate $H$ with Planck time $t_P$, larger than standard inflaton fluctuations. Current measurements of the spectrum are used to derive constraints on parameters of the effective potential in a slow-roll background. It is shown that spooky nonlocality can create statistically homogeneous and isotropic primordial curvature perturbations that are initially directionally antisymmetric. New statistical estimators are developed to study unique signatures in CMB anisotropy and large scale galaxy surveys.

Hubble flow variations as a test for inhomogeneous cosmology

Context.Backreactions from large-scale inhomogeneities may provide an elegant explanation for the observed accelerated expansion of the universe without the need to introduce dark energy.Aims.We propose a cosmological test for a specific model of inhomogeneous cosmology, called timescape cosmology. Using large-scale galaxy surveys such as SDSS and 2MRS, we test the variation of expansion expected in the Λ-cold dark matter (Λ-CDM) model versus a more generic differential expansion using our own calibrations of bounds suggested by timescape cosmology.Methods.Our test measures the systematic variations of the Hubble flow towards distant galaxies groups as a function of the matter distribution in the lines of sight to those galaxy groups. We compare the observed systematic variation of the Hubble flow to mock catalogues from the Millennium Simulation in the case of the Λ-CDM model, and a deformed version of the same simulation that exhibits more pronounced differential expansion.Results.We perform a series of statistical tests, ranging from linear regressions to Kolmogorov-Smirnov tests, on the obtained data. They consistently yield results preferring Λ-CDM cosmology over our approximated model of timescape cosmology.Conclusions.Our analysis of observational data shows no evidence that the variation of expansion differs from that of the standard Λ-CDM model.

Dark matter statistics for large galaxy catalogues: power spectra and covariance matrices

Upcoming and existing large-scale surveys of galaxies require accurate theoretical predictions of the dark matter clustering statistics for thousands of mock galaxy catalogs. We demonstrate that this goal can be achieve with our new Parallel Particle-Mesh (PM) Nbody code (PPM-GLAM) at a very low computational cost. We run about 15,000 simulations with ~2 billion particles that provide ~1% accuracy of the dark matter power spectra P(k) for wave-numbers up to k~ 1h/Mpc. Using this large data-set we study the power spectrum covariance matrix, the stepping stone for producing mock catalogs. In contrast to many previous analytical and numerical results, we find that the covariance matrix normalised to the power spectrum C(k,k')/P(k)P(k') has a complex structure of non-diagonal components. It has an upturn at small k, followed by a minimum at k=0.1-0.2h/Mpc. It also has a maximum at k=0.5-0.6h/Mpc. The normalised covariance matrix strongly evolves with redshift: C(k,k')~delta(t)^alpha P(k)P(k'), where delta is the linear growth factor and alpha ~ 1-1.25, which indicates that the covariance matrix depends on cosmological parameters. We also show that waves longer than 1Gpc have very little impact on the power spectrum and covariance matrix. This significantly reduces the computational costs and complexity of theoretical predictions: relatively small volume ~ (1Gpc)^3 simulations capture the necessary properties of dark matter clustering statistics. All the power spectra obtained from many thousands of our simulations are publicly available.

Subhalo Abundance Matching in f(R) Gravity.

Using the liminality N-body simulations of Shi etal., we present the first predictions for galaxy clustering in f(R) gravity using subhalo abundance matching. We find that, for a given galaxy density, even for an f(R) model with f_{R0}=-10^{-6}, for which the cold dark matter clustering is very similar to the cold dark matter model with a cosmological constant (ΛCDM), the predicted clustering of galaxies in the f(R) model is very different from ΛCDM. The deviation can be as large as 40% for samples with mean densities close to that of L_{*} galaxies. This large deviation is testable given the accuracy that future large-scale galaxy surveys aim to achieve. Our result demonstrates that galaxy surveys can provide a stringent test of general relativity on cosmological scales, which is comparable to the tests from local astrophysical observations.

Combining cluster number counts and galaxy clustering

The abundance of clusters and the clustering of galaxies are two of the important cosmological probes for current and future large scale surveys of galaxies, such as the Dark Energy Survey. In order to combine them one has to account for the fact that they are not independent quantities, since they probe the same density field. It is important to develop a good understanding of their correlation in order to extract parameter constraints. We present a detailed modelling of the joint covariance matrix between cluster number counts and the galaxy angular power spectrum. We employ the framework of the halo model complemented by a Halo Occupation Distribution model (HOD). We demonstrate the importance of accounting for non-Gaussianity to produce accurate covariance predictions. Indeed, we show that the non-Gaussian covariance becomes dominant at small scales, low redshifts or high cluster masses. We discuss in particular the case of the super-sample covariance (SSC), including the effects of galaxy shot-noise, halo second order bias and non-local bias. We demonstrate that the SSC obeys mathematical inequalities and positivity. Using the joint covariance matrix and a Fisher matrix methodology, we examine the prospects of combining these two probes to constrain cosmological and HOD parameters. We find that the combination indeed results in noticeably better constraints, with improvements of order 20% on cosmological parameters compared to the best single probe, and even greater improvement on HOD parameters, with reduction of error bars by a factor 1.4-4.8. This happens in particular because the cross-covariance introduces a synergy between the probes on small scales. We conclude that accounting for non-Gaussian effects is required for the joint analysis of these observables in galaxy surveys.

A new method to quantify the effects of baryons on the matter power spectrum

Future large-scale galaxy surveys have the potential to become leading probes for cosmology provided the influence of baryons on the total mass distribution is understood well enough. As hydrodynamical simulations strongly depend on details in the feedback implementations, no unique and robust predictions for baryonic effects currently exist. In this paper we propose a baryonic correction model that modifies the density field of dark-matter-only N-body simulations to mimic the effects of baryons from any underlying adopted feedback recipe. The model assumes haloes to consist of 4 components: 1- hot gas in hydrostatical equilibrium, 2- ejected gas from feedback processes, 3- central galaxy stars, and 4- adiabatically relaxed dark matter, which all modify the initial dark-matter-only density profiles. These altered profiles allow to define a displacement field for particles in N-body simulations and to modify the total density field accordingly.The main advantage of the baryonic correction model is to connect the total matter density field to the observable distribution of gas and stars in haloes, making it possible to parametrise baryonic effects on the matter power spectrum. We show that the most crucial quantities are the mass fraction of ejected gas and its corresponding ejection radius. The former controls how strongly baryons suppress the power spectrum, while the latter provides a measure of the scale where baryonic effects become important. A comparison with X-ray and Sunyaev-Zel'dovich cluster observations suggests that baryons suppress wave modes above k∼0.5 h/Mpc with a maximum suppression of 10-25 percent around k∼ 2 h/Mpc. More detailed observations of the gas in the outskirts of groups and clusters are required to decrease the large uncertainties of these numbers.

Scale-dependent bias from an inflationary bispectrum: the effect of a stochastic moving barrier

With the advent of large scale galaxy surveys, constraints on primordial non-Gaussianity (PNG) are expected to reach ${\cal O}(f_\text{NL}) \sim 1$. In order to fully exploit the potential of these future surveys, a deep theoretical understanding of the signatures imprinted by PNG on the large scale structure of the Universe is necessary. In this paper, we explore the effect of a stochastic moving barrier on the amplitude of the non-Gaussian bias induced by local quadratic PNG. We show that, in the peak approach to halo clustering, the amplitude of the non-Gaussian bias will generally differ from the peak-background split prediction unless the barrier is flat and deterministic. For excursion set peaks with a square-root barrier, which reproduce reasonably well the linear bias $b_1$ and mass function $\bar{n}_\text{h}$ of SO haloes, the non-Gaussian bias amplitude is $\sim 40$% larger than the peak-background split expectation $d\ln\bar{n}_\text{h}/d\ln\sigma_8$ for haloes of mass $\sim 10^{13} {\it h}^{-1}M_\odot$ at $z=0$. Furthermore, we argue that the effect of PNG on squeezed configurations of the halo bispectrum differs significantly from that predicted by standard local bias approaches. Our predictions can be easily confirmed, or invalidated, with N-body simulations.

A cosmological exclusion plot: towards model-independent constraints on modified gravity from current and future growth rate data

Most cosmological constraints on modified gravity are obtained assuming that the cosmic evolution was standard ΛCDM in the past and that the present matter density and power spectrum normalization are the same as in a ΛCDM model. Here we examine how the constraints change when these assumptions are lifted. We focus in particular on the parameter Y (also called Geff) that quantifies the deviation from the Poisson equation. This parameter can be estimated by comparing with the model-independent growth rate quantity fσ8(z) obtained through redshift distortions. We reduce the model dependency in evaluating Y by marginalizing over σ8 and over the initial conditions, and by absorbing the degenerate parameter Ωm,0 into Y. We use all currently available values of fσ8(z). We find that the combination Ŷ=YΩm,0, assumed constant in the observed redshift range, can be constrained only very weakly by current data, Ŷ=0.28−0.23+0.35 at 68% c.l. We also forecast the precision of a future estimation of Ŷ in a Euclid-like redshift survey. We find that the future constraints will reduce substantially the uncertainty, Ŷ=0.30−0.09+0.08 , at 68% c.l., but the relative error on Ŷ around the fiducial remains quite high, of the order of 30%. The main reason for these weak constraints is that Ŷ is strongly degenerate with the initial conditions, so that large or small values of Ŷ are compensated by choosing non-standard initial values of the derivative of the matter density contrast.Finally, we produce a forecast of a cosmological exclusion plot on the Yukawa strength and range parameters, which complements similar plots on laboratory scales but explores scales and epochs reachable only with large-scale galaxy surveys. We find that future data can constrain the Yukawa strength to within 3% of the Newtonian one if the range is around a few Megaparsecs. In the particular case of f(R) models, we find that the Yukawa range will be constrained to be larger than 80 Mpc/h or smaller than 2 Mpc/h (95% c.l.), regardless of the specific f(R) model.